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Prediction of Heart Failure Decompensation Events by Trend Analysis of Telemonitoring Data., , , , , , и . IEEE J. Biomed. Health Informatics, 19 (5): 1757-1769 (2015)A non-exercise based V02max prediction using FRIEND dataset with a neural network., , , , , , , , , и 2 other автор(ы). EMBC, стр. 4203-4206. IEEE, (2017)Telehealth streams reduction based on pattern recognition techniques for events detection and efficient storage in EHR., , , и . EMBC, стр. 7488-7491. IEEE, (2013)Improvement of CVD risk assessment tools' performance through innovative patients' grouping strategies., , , , , , и . EMBC, стр. 5907-5910. IEEE, (2012)Improving the compromise between accuracy, interpretability and personalization of rule-based machine learning in medical problems., , и . CoRR, (2021)Expert knowledge integration in the data mining process with application to cardiovascular risk assessment., , , , , , , и . EMBC, стр. 2538-2542. IEEE, (2015)Latent states extraction through Kalman Filter for the prediction of heart failure decompensation events., , , , , , , и . EMBC, стр. 3947-3950. IEEE, (2019)Multi-parametric prediction for cardiovascular risk assessment., , , , и . pHealth, том 224 из Studies in Health Technology and Informatics, стр. 15-20. IOS Press, (2016)An efficient strategy for evaluating similarity between time series based on Wavelet / Karhunen-Loève transforms., , , и . EMBC, стр. 6216-6219. IEEE, (2012)Assessment of cardiovascular risk based on a data-driven knowledge discovery approach., , , , , , и . EMBC, стр. 6800-6803. IEEE, (2015)